As embodied intelligence (EI), large language models (LLMs), and cloud computing continue to advance, Industry 5.0 facilitates the development of industrial art
This paper provides a systematic review of emerging control techniques used for railway Virtual Coupling (VC) studies. Train motion models are first reviewed, including model formulations and the force elements involved. Control objectives and typical design constraints are then elaborated. Next, the existing VC control techniques are surveyed and classified into five groups: consensus-based control, model prediction control, sliding mode control, machine learning-based control, and constraints-following control. Their advantages and disadvantages for VC applications are also discussed in detail. Furthermore, several future studies for achieving better controller development and implementation, respectively, are presented. The purposes of this survey are to help researchers to achieve a better systematic understanding regarding VC control, to spark more research into VC and to further speed-up the realization of this emerging technology in railway and other relevant fields such as road vehicles.
This paper deals with the problem of distributed formation tracking control and obstacle avoidance of multi-vehicle systems (MVSs) in complex obstacle-laden environments. The MVS under consideration consists of a leader vehicle with an unknown control input and a group of follower vehicles, connected via a directed interaction topology, subject to simultaneous unknown heterogeneous nonlinearities and external disturbances. The central aim is to achieve effective and collision-free formation tracking control for the nonlinear and uncertain MVS with obstacles encountered in formation maneuvering, while not demanding global information of the interaction topology. Toward this goal, a radial basis function neural network is used to model the unknown nonlinearity of vehicle dynamics in each vehicle and repulsive potentials are employed for obstacle avoidance. Furthermore, a scalable distributed adaptive formation tracking control protocol with a built-in obstacle avoidance mechanism is developed. It is proved that, with the proposed protocol, the resulting formation tracking errors are uniformly ultimately bounded and obstacle collision avoidance is guaranteed. Comprehensive simulation results are elaborated to substantiate the effectiveness and the promising collision avoidance performance of the proposed scalable adaptive formation control approach.
This paper is concerned with networked output feedback H <inf xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">∞</inf> control of an offshore structure under earthquakes. With a networked model of the offshore structure, a networked output feedback H <inf xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">∞</inf> control strategy is proposed to suppress seismic vibration of the structure. Then, some delay-dependent stability criteria for the offshore structure system are derived. Simulation results show that compared with traditional network-free controllers, the networked output feedback H <inf xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">∞</inf> controller can mitigate vibration of the offshore structure and control cost to a smaller level.
DeepSeek, a Chinese artificial intelligence (AI) startup, has released their V3 and R1 series models, which attracted global attention due to their low cost, hi
This chapter is concerned with the cooperative target trackingTarget tracking of multiple UMVsUnmanned Marine Vehicles (UMVs) under switching network topologies. For the target to be tracked, only its position can be measured/received by some of the UMVsUnmanned Marine Vehicles (UMVs), and its velocity is unavailable to all the UMVsUnmanned Marine Vehicles (UMVs). A distributed extended state observer considering switching topologiesSwitching topologies is designed to integrally estimate unknown target dynamics and neighboring UMVs'Unmanned Marine Vehicles (UMVs) dynamics. Accordingly, a novel kinematic controller is designed, which takes full advantage of known information and avoids the approximation of some virtual control vectors. Moreover, a disturbance observer is presented to estimate unknown time-varying environmental disturbances. Furthermore, a distributed dynamic controller is designed to regulate the involved UMVsUnmanned Marine Vehicles (UMVs) to cooperatively track the target.
This paper is concerned with the problem of robust output feedback controller design for a class of linear discrete-time systems with normbounded uncertainty. The objective is to design a controller such that the closed-loop poles are assigned within a specified disc and the steady regulated output covariance is guaranteed to be less than a given upper bound. Using a linear matrix inequality (LMI) approach, the existence conditions of such controllers are derived, and a parametrized characterization of a set of desired controllers (if they exist) is presented in terms of the feasible solutions to a set of LMIs. A procedure is given to select a suitable output feedback controller that minimizes the desired control effort.
This article deals with the proportional–integral observer (PIO) design problem for a class of linear systems with distributed time delays and randomly occurring parameter uncertainties. The measurement signals, transmitted from the sensors to the observer, might suffer from the randomly occurring deception attacks. The random occurrences of parameter uncertainties and deception attacks are governed by two series of Bernoulli random variables with known probability distributions. An outlier-resistant PIO is developed by introducing an innovation saturation mechanism for the sake of alleviating the adverse effects induced by the deception attacks on the estimation performance. The purpose of the addressed problem is to design a PIO that is capable of guaranteeing the mean-square boundedness of the estimation errors while achieving the desired security level. The desired PIO gain is designed by solving a matrix inequality and the validity of the results obtained is shown by a numerical simulation example.
This paper is concerned with the problem of designing distributed event-triggered H <inf xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">∞</inf> filters over sensor networks subject to heterogeneous coupling intercommunication delays. A new distributed event-triggered scheme is proposed to determine whether or not each sensor's current sampled data should be broadcasted and transmitted to its underlying neighboring nodes through the communication network. In this scheme, each sensor node is able to make its own decisions to broadcast and transmit only when its local measurement output error exceeds a designed threshold. Heterogeneous coupling delays are incorporated in the intercommunication between the specific sensor node and its interacting neighbors. A refined technique is proposed to realize the complicated decoupling among the exchanged measurement outputs in the presence of coupling intercommunication delays. Then the resulting filter error system is modeled by a new delay system subject to finite time-varying "state" delays. Based on the Lyapunov-Krasovskii functional method, a sufficient condition for distributed event-triggered H <inf xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">∞</inf> filter design is established, from which the desired filter parameters and the triggering parameter in the event condition can be co-designed. The filter design problem is posed in terms of linear matrix inequalities. A quarter-car suspension model is finally presented to show the effectiveness and feasibility of the developed theoretical results.
This is the first book to comprehensively and systematically discuss optimal control, sliding mode control, delayed feedback control, and network-based control schemes for offshore platforms, and to present the latest advances in these control schemes.
This paper deals with the distributed fault detection for discrete-time Markov jump linear systems over sensor networks with Markovian switching topologies. The sensors are scatteredly deployed in the sensor field and the fault detectors are physically distributed via a communication network. The system dynamics changes and sensing topology variations are modeled by a discrete-time Markov chain with incomplete mode transition probabilities. Each of these sensor nodes firstly collects measurement outputs from its all underlying neighboring nodes, processes these data in accordance with the Markovian switching topologies, and then transmits the processed data to the remote fault detector node. Network-induced delays and accumulated data packet dropouts are incorporated in the data transmission between the sensor nodes and the distributed fault detector nodes through the communication network. To generate localized residual signals, mode-independent distributed fault detection filters are proposed. By means of the stochastic Lyapunov functional approach, the residual system performance analysis is carried out such that the overall residual system is stochastically stable and the error between each residual signal and the fault signal is made as small as possible. Furthermore, a sufficient condition on the existence of the mode-independent distributed fault detection filters is derived in the simultaneous presence of incomplete mode transition probabilities, Markovian switching topologies, network-induced delays, and accumulated data packed dropouts. Finally, a stirred-tank reactor system is given to show the effectiveness of the developed theoretical results.
This paper is concerned with output feedback stabilization of a networked control system in the discrete-time domain. First, a logical zero-order-hold is introduced to select the newest data packets to drive the plant, with which network-induced delays and data packet dropouts can be expressed explicitly. Second, an auxiliary vector-valued function is introduced to establish a novel finite-sum inequality, which can provide a tighter bound than some existing ones for some finite-sum term. Third, this finite-sum inequality is employed to formulate a stability criterion for the closed-loop system under consideration. It is proven that the stability criterion is of less conservatism than some existing ones reported in the literature. Fourth, a cone-complementary-linearization-based algorithm is presented to design suitable output feedback controllers. Finally, three examples are given to show the effectiveness of the proposed method.
This paper focuses on the network-based modeling and proportional-integral (PI) control for a continuous-time direct-drive-wheel system in a wireless network environment. The developed system can simplify configuration, reduce bus cables, and realize vehicle height adjustment. A novel network-based model is first established by constructing a PI control system and taking network-induced delays and stochastic packet dropouts into account. By using two different artificial delays to characterize the update of proportional and integral control signals, the network-based PI control system is modeled as a stochastic impulsive system with two input delays and reset equations at updating instants. Then, through involving the reset states and the relationship among two delayed states and the current state in the discontinuous Lyapunov-Krasovskii functional and actively introducing the upper bounds of nonzero network-induced delays, some exponential mean-square stability and H <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">∞</sub> performance conditions with less conservatism are derived in terms of tractable linear matrix inequalities. An algorithm is presented to determine the minimum H <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">∞</sub> performance and the corresponding PI control parameters by combining a particle swarm optimization technique with the performance condition. These results can be extended to a network-based PI control of general continuous-time linear systems. A ZigBee-based network simulation platform is finally built and some simulation results are provided to validate the proposed methods.
This article addresses the problem of cooperative control of double-integrator type multirobot systems. Different from some conventional results with the control gain explicitly known, the control gain in this article is subject to uncertainty. Three different collective behaviors are explored, i.e., leaderless consensus, leader-following consensus, and formation control. For leaderless consensus, a sliding variable is constructed, based on which a novel continuous controller is designed such that the sliding surface is reached in finite-time and thus the state agreement of all agents is realized. For leader-following consensus, two different cases are investigated, i.e., the leader with constant velocity and with time-varying velocity. In both cases, sliding-mode based controllers are developed and corresponding stability conditions are established to ensure that the leader state is tracked by all followers. Finally, the theoretical results are applied to achieve formation control of nonholonomic mobile robots and corresponding experimental studies are conducted to demonstrate the effectiveness of the proposed controllers.
In this article, we provide a review of the consensus control problem for stochastic multi-agent systems (MASs). Recent advances are surveyed according to
Identifying Internet-facing industrial control system (ICS) devices is important for asset inventory, vulnerability assessment, exposure measurement, and security monitoring. This dataset release supports research on network traffic fingerprinting for Internet-facing ICS devices under realistic measurement conditions. The dataset is constructed from Internet-scale ICS service discovery followed by protocol-specific probing across three commonly deployed ICS protocols: Modbus/TCP, EtherNet/IP, and S7comm. It contains anonymized network traffic, scanning logs, device information records, and protocol-specific scanner code used to document the measurement logic. The release covers 13,002 responsive Internet-facing ICS endpoints, including 2,205 labeled endpoints spanning 20 vendors, 8 device types, and 165 device models. The measurements are organized across three collections and 60 scanning rounds for each protocol. The dataset captures Internet-facing measurement characteristics that are rarely represented in testbed datasets, including long-tailed label distributions, response variability across scanning rounds, temporal variation, and scanner-location effects. These characteristics support empirical studies of device fingerprint generation, vendor/type/model identification, and robustness to Internet-facing measurement variability. All released IP addresses are anonymized using a consistent prefix-preserving transformation, allowing cross-file linkage across device information, packet captures, and scanning logs without exposing the original public endpoints.
